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Comparing Occam and Wiener Filters on Broad-Band Signals

Natarajan, Balas K.; Konstantinides, Konstantinos

HPL-94-82

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Abstract: Occam filters are a class of filters for additive random noise, based on the idea that when lossy data compression algorithm is applied to a noisy signal with the allowed loss set equal to the noise strength, the loss and the noise tend to cancel rather than add. In this paper, we apply non-linear Occam filters to broad-band signals. Using the chirp signal as a specific example, we find that the Occam filter outperforms the Wiener filter consistently.

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